Key findings

How many people are outsourced?

1 in 6 (17%) of UK workers are outsourced.¹

In terms of the the different possible types of outsourced groups², the numbers are as follows:

1. Definitely outsourced: 11%
2. Likely agency: 3%
3. High indicators: 3%

Characteristics of outsourced workers

Age

Outsourced workers are on average younger than non-outsourced workers. The median age of the outsourced group is 36 , compared to 43 for the not outsourced group.³ This difference is statistically significant (t(2399.2) = 11.95, p = 0).

Outsourcing group	Mean	Median	Min	Max	Standard dev.	N
Not outsourced	42.80	43	16	80	13.08	8472
Outsourced	38.63	36	16	78	13.07	1683

The higher concentration of younger workers identified above appears to be driven primarily by the ‘outsourced’ and ‘high indicator’ groups, whilst the ‘likely agency’ group follows a similar pattern to the non-outsourced group.⁴

Outsourcing group	Mean	Median	Min	Max	Standard dev.	N
Not outsourced	42.80	43	16	80	13.08	8472
Outsourced	38.40	35	16	78	13.09	1123
Likely agency	39.80	38	18	77	13.49	269
High indicators	38.49	35	18	72	12.55	291

Gender

# weights:  12 (6 variable)
initial  value 14077.819237 
iter  10 value 7610.573378
iter  20 value 7465.550476
final  value 7465.517316 
converged

The outsourced workforce consists of a greater proportion of males than the non-outsourced workforce.⁵ Men make up 56% of the outsourced workforce compared to 47% of the non-outsourced workforce. This difference is statistically significant; outsourced workers, compared to non-outsourced workers, are 1.44 times more likely to be male than female.⁶

# weights:  20 (12 variable)
initial  value 14077.819237 
iter  10 value 7977.307669
iter  20 value 7461.899083
iter  30 value 7457.852026
iter  40 value 7457.374598
final  value 7457.362521 
converged

Breaking down by outsourcing group, we find that the group with the largest proportion of men in the workforce is the ‘high indicators’ group (66.35%), followed by the ‘likely agency’ group (56.66%), followed by the ‘outsourced’ group (53.94%). Statistically speaking, compared to a not outsourced person,

• Someone in the high indicators group is 2.18 times more likely to be male than female.
• Someone in the likely agency group is 1.45 times more likely tobe male than female.
• Someone in the outsourced group is 1.31 times more likely tobe male than female.

Additionally, people identifying as ‘Other’ gender are absent from the high indicators and likely agency groups, though given the small N (14) for this group, this finding is unlikely to be meaningful.

Ethnicity

People from an ethnic minority are 1.83 times more likely to be outsourced than people from a White British background; 33.09% of outsourced workers are from an ethnic minority, compared to 21.99% of non-outsourced workers.⁷

Comparison of ethnicities indicates that some groups are statistically more likely to be outsourced than others⁸:

• White other workers are 1.43 times more likely than White workers to be outsourced.
• Black African workers are 2.75 times more likely than White workers to be outsourced.
• Mixed other workers are 2.19 times more likely than White workers to be outsourced.
• South Asian workers are 2.25 times more likely than White workers to be outsourced.
• Other workers are 1.62 times more likely than White workers to be outsourced.
• Black other workers are 2.66 times more likely than White workers to be outsourced.
• Arab workers are 3.39 times more likely than White workers to be outsourced.

White other, Black Caribbean, and East Asian workers are no more or less likely than White workers to be outsourced.

# weights:  44 (30 variable)
initial  value 14077.819237 
iter  10 value 6005.031007
iter  20 value 5973.065586
iter  30 value 5972.625912
final  value 5972.625599 
converged

Breaking down by outsourcing group helps to separate out the type of outsourced work people from the ethnicities identified above engage in.⁹ Compared to White British workers,

• White other workers are more likely to be outsourced than not outsourced
• Black African workers are more likely to be outsourced, likely agency, or high indicators than not outsourced
• Mixed other workers are more likely to be likely agency workers than not outsourced
• South Asian workers are more likely to be outsourced, likely agency, or high indicators than not outsourced
• Other workers are more likely to be outsourced or likely agency than not outsourced
• Black other workers are more likely to be outsourced than not outsourced
• Arab workers are more likely to be likely agency or high indicators than not outsourced

Interaction: Ethnicity and gender

There does not appear to be any compelling ethnicity by gender interaction. There is a marginally significant effect indicating that East Asian men, but not East Asian women, are less likely to be outsourced than their White British counterparts.

Arrival in the UK

As for non-outsourced workers, the vast majority of outsourced workers are born in the UK. However, people not born in the UK are more likely to be outsourced than people born in the UK. 24.13% of outsourced workers are not born in the UK, compared to 14.08% of non-outsourced workers.¹⁰ This difference is statistically significant; outsourced workers are 1.94 times more likely to have been born outside the UK than non-outsourced workers.¹¹

Note

This variable is worded a little strangely, e.g. responses are things like “within the last 10 years”, “within the last 15 years”. Given that respondents only give one answer to this question, I think we can assume that the responses are basically brackets. That is, someone responding “within the last 15 years” is basically saying “I came to the UK between 11 and 15 years ago”.

Looking at the figure below, compared to non-outsourced people, there is a larger proportion of outsourced workers for each arrival time apart from ‘Within the last 30 years’.

# weights:  12 (6 variable)
initial  value 14077.819237 
iter  10 value 6002.136126
final  value 6002.013178 
converged

Exploring types of outsourced work indicates that the pattern observed above applies evenly to the different outsourcing groups.¹² Compared to people born in the UK, people not born in the UK are:

• 1.97 times more likely to be outsourced than non-outsourced
• 1.82 times more likely to be likely agency than non-outsourced
• 1.93 times more likely to be high indicators than non-outsourced

The figure below indicates that the proportion of workers of each outsourcing group within each arrival time are broadly similar.

Interaction: Ethnicity and arrival time

Analysis of Deviance Table

Model 1: outsourcing_status ~ Ethnicity_collapsed + BORNUK_binary
Model 2: outsourcing_status ~ Ethnicity_collapsed * BORNUK_binary
  Resid. Df Resid. Dev Df Deviance     F  Pr(>F)   
1     10144     9036.1                             
2     10135     9011.6  9   24.456 2.712 0.00373 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Exploring the intersection of ethnicity and arrival time reveals some patterns whereby the likelihood of a person being outsourced is related to the combinations of ethnicity and whether they were born in the UK.¹³ The plot below shows that

• Among workers born in the UK, a Black African worker is 2.73 times more likely to be outsourced than a White worker.
• Among workers born in the UK, a South Asian worker is 2.42 times more likely to be outsourced than a White worker.
• Among workers not born in the UK, a Black African worker is 1.97 times more likely to be outsourced than a White other worker.

Similarly, the plot below shows that¹⁴

• Among White workers, someone not born in the UK is 2.32 times more likely to be outsourced than someone born in the UK.
• Among Mixed other workers, someone not born in the UK is 2.84 times more likely to be outsourced than someone born in the UK.
• Among Other workers, someone not born in the UK is 1.64 times more likely to be outsourced than someone born in the UK.

Put differently, being born in the UK is relevant in predicting outsourcing status only for White, Mixed other, and Other ethnicities. For other ethnicities, it doesn’t matter whether you are born in the UK or not. And compared to a White person born in the UK, Black African and South Asian workers are more likely to be outsourced whether or not they were born in the UK.

Overall, this pattern of results paints a racialised picture with strong colonial undertones. UK-born Black African and South Asian workers are more likely than UK-born White workers to be outsourced. For these and most other non-White groups, being born in the UK is not relevant for predicting outsourcing status; a Black African is just as likely to be outsourced if they arrived in the UK today than if they were born in the UK. However, the story is not one only of race. Non-UK-born White people are more likely to be outsourced than UK-born White people.

In summary, people born in the UK are more likely to be outsourced if they are Black African or South Asian compared to White, and White and (mixed) other ethnicities are more likely to be outsourced if they are not born in the UK compared to if they were born in the UK.

We next explore arrival time by collapsing responses to the arrival time question into fewer categories as below

Collapsed level	Original level
Born in UK	I was born in the UK
Came to UK recently	Within the last year Within the last 3 years Within the last 5 years Within the last 10 years
Came to UK not recently	Within the last 15 years Within the last 20 years Within the last 30 years More than 30 years ago
Prefer not to say	Prefer not to say

Exploring these categories¹⁵ confirms that

• Among workers born in the UK, a Black African worker is 2.73 times more likely to be outsourced than a White worker.

• Among workers born in the UK, a South Asian worker is 2.42 times more likely to be outsourced than a White worker.

And¹⁶

• Among White workers,

• Someone who came to the UK recently is 3.37 times more likely to be outsourced than someone born in the UK.

• Someone who came to the UK not recently is 1.85 times more likely to be outsourced than someone born in the UK.

• Someone who preferred to not say when they arrived is 2.32 times more likely to be outsourced than someone born in the UK.

• Among East Asian workers

  • Someone who came to the UK not recently is 3.61 times more likely to be outsourced than someone born in the UK.
  • Someone who came to the UK not recently is 11.91 times more likely to be outsourced than someone who came to the UK recently

• Among Other workers

  • Someone who came to the UK not recently is times more likely to be outsourced than someone born in the UK.

In summary,

• White outsourced workers are more likely to have not been born in the UK
• East Asian and Other outsourced workers are more likely to have been in the UK a longer time (10 years plus)
• UK-born Black African and South Asian workers are more likely to be outsourced than White UK-born workers, but no more or less likely to be outsourced than non-UK born Black African and South Asian workers (revise this)

Region

The plot below shows the proportion of workers within each region who are outsourced.¹⁷

Below we map the workforce composition in each region. The first map emphasises that London has the highest concentration of outsourced workers (25%).

The second map excludes London so that is easier to see how the remaining regions compare. After London, the regions with the highest proportion of outsourced workers are:

1. East Midlands (19%)
2. West Midlands (18%)
3. Wales (18%)
4. North West (17%)
5. Northern Ireland (16%)

We can also explore how the the entire UK workforce is distributed across the country.¹⁸ The table and map below show the percentage of outsourced workers in each region as a proportion of the total UK workforce. They show where the UK’s outsourced workforce is concentrated. The regions with the highest share of the UK’s outsourced workforce are:

1. London (21%)
2. North West (11%)
3. South East (11%)
4. West Midlands (9%)
5. East Midlands (8%)

Region	Frequency	Sum	Percentage
London	357.35	1708.36	20.92
North West	189.39	1708.36	11.09
South East	188.47	1708.36	11.03
West Midlands	161.49	1708.36	9.45
East Midlands	140.50	1708.36	8.22
Scotland	125.82	1708.36	7.37
East of England	125.49	1708.36	7.35
South West	120.50	1708.36	7.05
Yorkshire and the Humber	119.46	1708.36	6.99
Wales	83.25	1708.36	4.87
North East	53.06	1708.36	3.11
Northern Ireland	43.56	1708.36	2.55

Characteristics of outsourced work

Pay

Note

Note, the total sample on which income analysis is based is 8943.

The number of income data points for the outsourced group is 1512

The number of income data points for the not outsourced group is 7431

The table and plot below show descriptive statistics on income and its distribution for outsourced and non-outsourced people. Regression analysis shows that outsourced workers are on average paid £2048 less than non-outsourced workers.¹⁹

Outsourcing group	n	Mean	Median	Min	Max	Standard dev.
Not outsourced	6925	27106.73	25200.5	2000	66669	13309.13
Outsourced	1366	25058.37	24000.0	2400	66108	13022.18

This difference increases to £2954 when we take into account Age, Gender, Ethnicity, Region, and Arrival Time. ²⁰ This analysis shows that all other variables, apart from Age, are in some way relevant to income. On average,

• Men earn £6592 more than women.
• East Asian workers earn £6064 more than White British workers.
• Workers in all non-London regions earn less than workers in London
  • East Midlands: -£6549
  • East of England: -£4563
  • North East: -£5291
  • North West: -£4932
  • Northern Ireland: -£7192
  • Scotland: -£4959
  • South East: -£3940
  • Wales: -£5430
  • West Midlands: -£5764
  • Yorkshire and the Humber: -£6042
• People who arrived in the UK within the last year earn £3868 less than people born in the UK
• People who arrived within the last 30 years earn £3489 more than people born in the UK.

Notable takeaways:

• There is a substantial gender pay gap present in the data
• The South East is the highest-paid region after London. Northern Ireland is the lowest paid region.
• People who have very recently arrived in the UK are paid less than people who were born in the UK, whilst people who migrated to the UK a long time ago earn more than people born in the UK.

Next we explore differences by outsourcing group. The table and plot below show descriptive statistics on income and its distribution for outsourced groups. Regression analysis shows that outsourced workers are on average paid £2987 less than non-outsourced workers, while no differences are evident for the likely agency and high indicators groups.²¹

Outsourcing group	n	Mean	Median	Min	Max	Standard dev.
Not outsourced	6925	27106.73	25200.50	2000.00	66669.00	13309.13
Outsourced	896	24120.18	23000.00	2400.00	66000.00	12808.78
Likely agency	231	25639.33	23095.97	3569.28	65846.67	13754.83
High indicators	239	28286.45	27000.00	4644.00	65000.00	12631.89

However, when controlling, as before, for Age, Gender, Ethnicity, Arrival Time, and Region,²² we find

• the outsourced group on average earns £3643 less than the non-outsourced group, and
• the likely agency group on average earns £2272 less than the non-outsourced group

In addition to showing that likely agency workers receive lower pay than the non-outsourced workers, this analysis reveals that “pure outsourced” workers’ pay is even lower, and that the estimate we obtained in the analysis above considering only status is a diluted effect averaging the outsourced and likely agency pay gaps.

Income group

Call:
glm(formula = income_group ~ Age + Gender + Ethnicity_collapsed + 
    BORNUK_labelled + Region + outsourcing_status, family = "quasibinomial", 
    data = data, weights = NatRepemployees)

Coefficients:
                                         Estimate Std. Error t value
(Intercept)                             -0.920343   0.108909  -8.451
Age                                      0.004672   0.001799   2.598
GenderMale                              -1.043714   0.046118 -22.631
GenderOther                             -0.294434   0.553784  -0.532
GenderPrefer not to say                 -0.528088   0.433103  -1.219
Ethnicity_collapsedWhite other           0.176601   0.137240   1.287
Ethnicity_collapsedBlack Caribbean      -0.014901   0.207538  -0.072
Ethnicity_collapsedBlack African        -0.038117   0.164550  -0.232
Ethnicity_collapsedMixed other           0.295306   0.238495   1.238
Ethnicity_collapsedSouth Asian           0.049750   0.112262   0.443
Ethnicity_collapsedEast Asian           -0.604209   0.225604  -2.678
Ethnicity_collapsedOther                 0.024540   0.120088   0.204
Ethnicity_collapsedBlack other           0.431471   0.382395   1.128
Ethnicity_collapsedArab                 -0.884850   0.461815  -1.916
BORNUK_labelledWithin the last year      0.705394   0.200283   3.522
BORNUK_labelledWithin the last 3 years  -0.063392   0.184161  -0.344
BORNUK_labelledWithin the last 5 years  -0.319297   0.204641  -1.560
BORNUK_labelledWithin the last 10 years -0.139763   0.159727  -0.875
BORNUK_labelledWithin the last 15 years -0.336823   0.182079  -1.850
BORNUK_labelledWithin the last 20 years -0.486871   0.202343  -2.406
BORNUK_labelledWithin the last 30 years -0.590329   0.236582  -2.495
BORNUK_labelledMore than 30 years ago   -0.165259   0.170262  -0.971
BORNUK_labelledPrefer not to say         0.515124   0.317357   1.623
RegionEast Midlands                      1.066954   0.108616   9.823
RegionEast of England                    0.881919   0.103023   8.560
RegionNorth East                         0.965856   0.135087   7.150
RegionNorth West                         0.935999   0.099731   9.385
RegionNorthern Ireland                   1.128891   0.154655   7.299
RegionScotland                           0.901455   0.106625   8.454
RegionSouth East                         0.697292   0.094600   7.371
RegionSouth West                         0.987987   0.106273   9.297
RegionWales                              0.764031   0.128967   5.924
RegionWest Midlands                      0.883164   0.103996   8.492
RegionYorkshire and the Humber           1.000237   0.106478   9.394
outsourcing_statusOutsourced             0.387382   0.061492   6.300
                                                    Pr(>|t|)    
(Intercept)                             < 0.0000000000000002 ***
Age                                                  0.00940 ** 
GenderMale                              < 0.0000000000000002 ***
GenderOther                                          0.59496    
GenderPrefer not to say                              0.22276    
Ethnicity_collapsedWhite other                       0.19820    
Ethnicity_collapsedBlack Caribbean                   0.94276    
Ethnicity_collapsedBlack African                     0.81682    
Ethnicity_collapsedMixed other                       0.21567    
Ethnicity_collapsedSouth Asian                       0.65766    
Ethnicity_collapsedEast Asian                        0.00742 ** 
Ethnicity_collapsedOther                             0.83809    
Ethnicity_collapsedBlack other                       0.25921    
Ethnicity_collapsedArab                              0.05539 .  
BORNUK_labelledWithin the last year                  0.00043 ***
BORNUK_labelledWithin the last 3 years               0.73069    
BORNUK_labelledWithin the last 5 years               0.11873    
BORNUK_labelledWithin the last 10 years              0.38159    
BORNUK_labelledWithin the last 15 years              0.06437 .  
BORNUK_labelledWithin the last 20 years              0.01614 *  
BORNUK_labelledWithin the last 30 years              0.01260 *  
BORNUK_labelledMore than 30 years ago                0.33177    
BORNUK_labelledPrefer not to say                     0.10459    
RegionEast Midlands                     < 0.0000000000000002 ***
RegionEast of England                   < 0.0000000000000002 ***
RegionNorth East                           0.000000000000937 ***
RegionNorth West                        < 0.0000000000000002 ***
RegionNorthern Ireland                     0.000000000000314 ***
RegionScotland                          < 0.0000000000000002 ***
RegionSouth East                           0.000000000000185 ***
RegionSouth West                        < 0.0000000000000002 ***
RegionWales                                0.000000003253637 ***
RegionWest Midlands                     < 0.0000000000000002 ***
RegionYorkshire and the Humber          < 0.0000000000000002 ***
outsourcing_statusOutsourced               0.000000000312324 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasibinomial family taken to be 1.001136)

    Null deviance: 12018  on 8942  degrees of freedom
Residual deviance: 11179  on 8908  degrees of freedom
  (1212 observations deleted due to missingness)
AIC: NA

Number of Fisher Scoring iterations: 4

A generalised linear model indicates that a worker is more likely to be in the low income group if they are:

• Older
• Arrived in the last year
• Work in any region apart from London
• Outsourced

Sectors

Outsourcing status

Here we explore what proportion of workers in each sector are outsourced.²³

The plot below shows the proportion of outsourced and not outsourced workers within each sector. I.e. this is showing what sectors have higher and lower proportions of outsourced workers.

The table below shows the percentage of outsourced workers in each Sector, ordered descending by percentage. It shows that the top three Sectors with the highest proportion of outsourced workers are:

• ACTIVITIES OF HOUSEHOLDS AS EMPLOYERS; UNDIFFERENTIATED GOODS-AND SERVICES-PRODUCING ACTIVITIES OF HOUSEHOLDS FOR OWN US (note that N = 31)
• ADMINISTRATIVE AND SUPPORT SERVICE ACTIVITIES
• WATER SUPPLY; SEWERAGE, WASTE MANAGEMENT AND REMEDIATION ACTIVITIES

Note that for an undefined sector (‘Not found’) contained one of the largest proportions of outsourced workers (31% of workers in the ‘Not found’ category were outsourced).

A key takeaway here is that whereas the total outsourced population is 17%, this figure varies by sector, from 0% for Mining… and Extraterritoral organisations… all the way to 36% for Activities of households as employers, with 5 out 20 sectors having at least 20% of their workforce outsourced.

Exploring this by type of outsourced worker shows that for all sectors, the majority of outsourced workers fall into the ‘outsourced’ group.²⁴

The next most common group after ‘outsourced’ varies by sector. Many sectors have an almost even split of likely agency and high indicator groups. Sectors that are notable for having quite large likely agency proportions relative to high indicator propottions are:

• Construction
• Accommodation and food service activities
• Activities of households as employers (note N = 32)

In contrast, sectors with high proportion ‘high indicators’ relative to likely agency are:

• Other service activities
• Professional, scientific and technical activities
• Real estate activities

Variations in pay

The plot below shows the average income by sector.²⁵

A multilevel model predicting income from outsourcing status (accounting for other variables), with random intercetps and random slopes for outsourcing status by sector indicates overall a significant negative effect of outsourcing status; by this estimation people who are outsourced earn approximately £2774 less than people who are not outsourced. The random effects indicate that influence of being outsourced varies with sector. For people working in ‘Wholesale and retail trade’ and ‘accommodation and food serivce activities’, being outsourced is associated with higher pay than not being outsourced. Note that both of these sectors fall into the bottom three sectors overall for pay. For people working in ‘Information and communication’ and ‘Education’, being outsourced is associated with lower pay than not being outsourced.

Visual comparisons indicate that for the vast majority of sectors, outsourced people tend to be paid less than non-outsourced people. Exceptions to this are ‘Professional, scientific and technical activities’, ‘Financial and insurance activities’, ‘Wholesale retail and trade’, and ‘Arts, entertainment and recreation’.²⁶

Exploring variations in pay by outsourcing group shows that the ‘outsourced’ group is commonly paid less than the non-outsourced group, whilst the ‘high indicators’ group and, to a less extent, the ‘likely agency’ group, vary in terms of how they are paid relative to the non-outsourced group. For example, in ‘Human health and social work’ and ‘wholesale retail and trade’, the high indicators group is paid more, whilst the outsourced group is paid less, relative to the non-outsourced group.²⁷

Although a model predicting income from outsourcing status and income group (controlling for other variables) indicates that pay does not depend on an interaction between a person’s outsourcing status and income group, the plots below are informative in displaying variation by sector.²⁸

Major occupations

The plot below shows the proportion of each major occupation group that is outsourced.²⁹

Below these proportions are further broken down by outsourcing group.³⁰

Variations in pay

The plot below shows the average income by major occupation group.³¹

A multilevel model predicting income from outsourcing status (accounting for other variables), with random intercepts and random slopes for outsourcing status by major occupation indicates overall a significant negative effect of outsourcing status; by this estimation people who are outsourced earn approximately £1675 less than people who are not outsourced. The random effects indicate that influence of being outsourced varies with sector. People who work in ‘Sales and customer service’, ‘elementary occupations’ and ‘caring, leisure and other serivce occupations’ tend to have higher pay if they are outsourced vs not outsourced. People who work in ‘professional occupations’, ‘associate professional occupations’, and ‘managers, directors and senior officials’ are paid less if they are outsourced vs not outsourced.

Looking at absolute differences in pay by major occupation indicates that outsourced workers in most groups are paid less than non-outsourced workers.³²

Breaking this down by group indicates that there is variation between types of outsourcing in terms of pay. The ‘outsourced’ group is often (though not always) the least well-paid out of the outsourcing groups.³³

Again, although we find no evidence overall of a significant interaction between income group and outsourcing status on income, we can still visually explore the distinction between low vs not low income.³⁴ The plot below shows that whilst the pattern of outsourced workers being paid less in general holds, in the higher income group there are more instances of outsourced workers being paid more than non-outsourced workers, compared to the low income group. This suggests that at the higher end of the pay distribution, being outsourced can be more lucrative than not being outsourced. Indeed, for Elementary occupations, there is a clear divergence evident in the pattern; for high income workers, being outsourced increases average income, whereas for low income workers, being outsourced decreases average income.

Breaking down the above by outsourcing group (below) shows that in some cases this pattern holds for all types of outsourced workers, whereas for other major occupations the finanical benefit depends on the type of outsourcing.³⁵ For example, in ‘Sales and customer services’, only high income outsourced workers are better paid than non-outsourced workers. Similarly, only low income outsourced workers in elementary occupations are paid less than non-outsourced workers, while high indicator, low income workers are paid more.

Unit occupations

Examining what unit occupations outsourced workers can be found in reveals that outsourced workers tend to be concentrated in a specific cluster of occupations.³⁶ 42% of outsourced workers are located in the top 10 most common unit occupations. The top 15 unit occupations capture over 50% of the outsourced workforce, and 76% of the outsourced workforce are captured in 30 unit occupations (out of a total of 96). These thresholds are shown in the plot below where the blue lines intersect the red curve.

The top 10 unit occupations for outsourced workers are:

• Functional Managers and Directors
• Sales Assistants and Retail Cashiers
• Caring Personal Services
• Other Administrative Occupations
• Information Technology Professionals
• Elementary Cleaning Occupations
• Teaching Professionals
• Other Elementary Services Occupations
• Road Transport Drivers
• Nursing Professionals

For the outsourced subgroup, 42% of workers are located in the top 10 most common unit occupations. The top 15 unit occupations capture 54% of the outsourced workforce, and 76% of the outsourced workforce are captured in 30 unit occupations (out of a total of 95).³⁷

For the outsourced subgroup, the top 10 occupations are almost identical to those of outsourcing as a whole:

• Functional Managers and Directors
• Sales Assistants and Retail Cashiers
• Caring Personal Services
• Elementary Cleaning Occupations
• Information Technology Professionals
• Other Administrative Occupations
• Teaching Professionals
• Elementary Storage Occupations
• Nursing Professionals
• Other Elementary Services Occupations

The only difference being that ‘Elementary storage occupations’ replaces ‘Road Transport Drivers’ in the top 10.

For the ‘likely agency’ subgroup, 48% of workers are located in the top 10 most common unit occupations. The top 15 unit occupations capture 59% of the workforce, and 79% of the workforce are captured in 30 unit occupations (out of a total of 65).³⁸

For the likely agency subgroup, the top 10 occupations are:

• Caring Personal Services
• Other Administrative Occupations
• Functional Managers and Directors
• Sales Assistants and Retail Cashiers
• Information Technology Professionals
• Road Transport Drivers
• Nursing Professionals
• Other Elementary Services Occupations
• Teaching Professionals
• Administrative Occupations: Finance

For the ‘high indicators’ subgroup, 45% of workers are located in the top 10 most common unit occupations. The top 15 unit occupations capture 57% of the workforce, and 80% of the workforce are captured in 30 unit occupations (out of a total of 67).³⁹

For the high indicators subgroup, the top 10 occupations are:

• Functional Managers and Directors
• Sales Assistants and Retail Cashiers
• Caring Personal Services
• Other Elementary Services Occupations
• Engineering Professionals
• Road Transport Drivers
• Elementary Cleaning Occupations
• Other Administrative Occupations
• Teaching Professionals
• Information Technology Professionals

Unit occupations - by major occupation

Statistical analysis indicates that the pay differences are significant for the following major group codes:

• Managers, directors and senior officials: Outsourced workers earn on average £3422 less than non-outsourced workers.
• Associate professional occupations: Outsourced workers earn on average £3534 less than non-outsourced workers.
• Professional occupations: Outsourced workers earn on average £3092 less than non-outsourced workers.
• Caring, leisure and other service occupations: Outsourced workers earn on average £1888 less than non-outsourced workers.
• Process, plant and machine operatives: Outsourced workers earn on average £3390 less than non-outsourced workers.

Next, for each of these major group codes, we explore the pay differences within each Unit Occupation.

Managers, directors and senior officials

The plot below suggests that the main driver of the effect in this major occupation group is in the ‘Functional Managers and Directors’ unit occupation; on average, outsourced workers in this group earn £4114 less than non-outsourced workers.⁴⁰

By outsourcing group

Breaking down by outsourcing group shows that most workers are outsourced in the ‘Functional managers and directors’ group, although a small number are likely agency.⁴¹

Associate professional occupations

The plot below indicates there are many unit occupations in this major occupation group where outsourced workers are paid less. The most notable of these are ‘Information and Technology Technicians’, ‘Business Associate Professionals’, and ‘Sales, Marketing and Related Associate Professionals’.⁴²

By outsourcing group

The plot below shows that the pattern above is mainly driven by people in the ‘outsourced’ group.⁴³

Professional occupations

The plot above indicates there are many unit occupations in this major occupation group where outsourced workers are paid less. The most notable of these are ‘Teaching professionals’, ‘Information Technology Professionals’, ‘Nursing Professionals’, ‘Finance Professionals’, ‘Business, Research and Admin Professionals’, and ‘Other Health Professionals’. An exception to the pattern is ‘Engineering Professionals’, where outsourced workers are paid more than non-outsourced workers.⁴⁴

By outsourcing group

Examining by outsourcing group indicates that the outsourced group is the main driver of lower pay in the identified unit occupations.⁴⁵

Caring, leisure and other service occupations

For this major occupation group, the notable differences in pay are in ‘Caring Personal services and ’Teaching and Childcare Support Occupations’.⁴⁶

By outsourcing group

Breaking down by outsourcing group shows that the outsourced and likely agency groups are paid less than non-outsourced workers. In contrast, for ‘Caring Personal Services’, workers in the ‘high indicators’ group tend to be paid more than non-outrsourced people (though note n = 13).⁴⁷

Process, plant and machine operatives

In this major occupation group, outsourced workers in most unit occupations are paid less than non-outsourced workers. The most notable here are ‘Road Transport Drivers’, ‘Assemblers and Routine Operatives’, and ‘Other Drivers and Transport Operatives’. In contrast, ‘Process Operatives’ tend to be paid more if they are outsourced. Note low Ns here.⁴⁸

By outsourcing group

Again, the outsourced group is the main driver of lower pay.⁴⁹

Summary

To summarise this section, we have identified five Major occupation groups where outsourced workers tend to be paid less than non-outsourced workers. These are:

• Managers, directors and senior officials: Outsourced workers earn on average £3422 less than non-outsourced workers.
• Associate professional occupations: Outsourced workers earn on average £3534 less than non-outsourced workers.
• Professional occupations: Outsourced workers earn on average £3092 less than non-outsourced workers.
• Caring, leisure and other service occupations: Outsourced workers earn on average £1888 less than non-outsourced workers.
• Process, plant and machine operatives: Outsourced workers earn on average £3390 less than non-outsourced workers.

When we investigate the unit occupations for each of these major group codes, we find that although there is some variation in the pattern, in general outsourced workers tend to be paid less than non-outsourced workers. Because the ‘outsourced’ group is the most common form of outsourced working, the finding of lower pay is mainly driven by this group. There are some instances of unit occupations where there are divergences between outsourced, likely agency, and high indicator groups, whereby, for example, likely agency workers are sometimes paid more than non-outsourced (and outsourced) workers, but due to low frequency counts, these patterns should be considered descriptive rather than inferential.

Footnotes

1. outputs/data/total_outsourced.csv

2. outputs/data/total_outsourced_2.csv

3. outputs/data/age_stats.csv

4. outputs/data/age_stats_2.csv

5. outputs/data/sector_summary_3.csv

6. ../outputs/data/gender_inferential_tab.csv

7. outputs/data/ethnicity_stats_1.csv & outputs/data/ethnicity_binary_o-status_inferential_tab.csv

8. outputs/data/ethnicity_model_inferential.csv

9. outputs/data/ethnicity_ogroup_inferential_tab.csv

10. outputs/data/arrival_in_UK_stats.csv

11. outputs/data/bornuk_ostatus_inferential_tab.csv

12. outputs/data/bornuk_ogroup_inferential_tab.csv & /outputs/data/arrival_in_UK_stats_2.csv

13. outputs/data/bornUK_binary_contrasts.csv

14. outputs/data/region_stats_2.csv

15. outputs/data/region_stats_3.csv

16. outputs/data/bornUK_collapsed_contrasts_2.csv

17. outputs/data/region_stats_2.csv

18. outputs/data/region_stats_3.csv

19. outputs/data/income_stats_o-status.csv & outputs/data/model_income_by_o-status.csv

20. outputs/data/model_2_income_by_o-status.csv

21. outputs/data/income_stats_o-group.csv & outputs/data/model_income_by_o-group.csv

22. outputs/data/model_2_income_by_o-group.csv

23. outputs/data/sector_summary_3.csv

24. outputs/data/sector_summary_o-group.csv

25. outputs/data/sector_summary_pay_overall.csv

26. outputs/data/sector_summary_pay.csv

27. outputs/data/sector_summary_o-group_pay.csv

28. outputs/data/sector_summary_paysplit_o-status.csv & outputs/data/sector_summary_paysplit_o-group_pay.csv

29. outputs/data/majorgroupcode_summary_o-status.csv

30. outputs/data/majorgroupcode_summary_o-group.csv

31. outputs/data/majorgroupcode_summary_pay_overall.csv

32. outputs/data/mgc_summary_pay.csv

33. outputs/data/mgc_summary_pay_group.csv

34. outputs/data/mgc_summary_paysplit.csv

35. outputs/data/mgc_summary_paysplit_group.csv

36. outputs/data/unit_occ_summary.csv

37. outputs/data/unit_occ_summary_outsourced_group.csv

38. outputs/data/unit_occ_summary_agency_group.csv

39. outputs/data/unit_occ_summary_indicators_group.csv

40. outputs/data/managers_unitoccs_summary_pay.csv

41. outputs/data/o-group_managers_unitoccs_summary_pay.csv

42. outputs/data/assoc-prof_unitoccs_summary_pay.csv

43. outputs/data/o-group_assoc-prof_unitoccs_summary_pay.csv

44. outputs/data/prof_unitoccs_summary_pay.csv

45. outputs/data/o-group_prof_unitoccs_summary_pay.csv

46. outputs/data/caring_unitoccs_summary_pay.csv

47. outputs/data/o-group_caring_unitoccs_summary_pay.csv

48. outputs/data/process_unitoccs_summary_pay.csv

49. outputs/data/o-group_process_unitoccs_summary_pay.csv